Pandas Profiling Report

Dataset statistics

Number of variables	36
Number of observations	1570
Missing cells	34827
Missing cells (%)	61.6%
Duplicate rows	48
Duplicate rows (%)	3.1%
Total size in memory	441.7 KiB
Average record size in memory	288.1 B

Variable types

Numeric	21
Categorical	13
Unsupported	2

Alerts

Dataset has 48 (3.1%) duplicate rows	Duplicates
`title` has a high cardinality: 257 distinct values	High cardinality
`author` has a high cardinality: 267 distinct values	High cardinality
`location` has a high cardinality: 102 distinct values	High cardinality
`Journal` has a high cardinality: 68 distinct values	High cardinality
`Excipients` has a high cardinality: 139 distinct values	High cardinality
`Additive_1` has a high cardinality: 124 distinct values	High cardinality
`title` has 628 (40.0%) missing values	Missing
`author` has 458 (29.2%) missing values	Missing
`location` has 486 (31.0%) missing values	Missing
`Journal` has 718 (45.7%) missing values	Missing
`material_0` has 126 (8.0%) missing values	Missing
`material_1` has 618 (39.4%) missing values	Missing
`Excipients` has 758 (48.3%) missing values	Missing
`Additive Species` has 1098 (69.9%) missing values	Missing
`Additive_1` has 1098 (69.9%) missing values	Missing
`Additive_2` has 1546 (98.5%) missing values	Missing
`Application Rate (%)` has 1262 (80.4%) missing values	Missing
`initial moisture content(%)` has 509 (32.4%) missing values	Missing
`initial pH` has 596 (38.0%) missing values	Missing
`initial TN(%)` has 992 (63.2%) missing values	Missing
`initial TC(%)` has 1012 (64.5%) missing values	Missing
`initial CN(%)` has 453 (28.9%) missing values	Missing
`TN loss (%)` has 1007 (64.1%) missing values	Missing
`NH3-N loss (%)` has 733 (46.7%) missing values	Missing
`N2O-N loss (%)` has 999 (63.6%) missing values	Missing
`TC loss (%)` has 1132 (72.1%) missing values	Missing
`CH4-C loss (%)` has 1081 (68.9%) missing values	Missing
`CO2-C loss (%)` has 1366 (87.0%) missing values	Missing
`Methods` has 711 (45.3%) missing values	Missing
`Time Period` has 905 (57.6%) missing values	Missing
`堆体大小（m3)` has 1422 (90.6%) missing values	Missing
`初始容重（kgL）` has 1433 (91.3%) missing values	Missing
`Ventilation` has 1156 (73.6%) missing values	Missing
`通风速率（L min-1 kg DW）` has 1287 (82.0%) missing values	Missing
`Peak Temperature (℃）` has 1445 (92.0%) missing values	Missing
`Average Temperature (℃）` has 1497 (95.4%) missing values	Missing
`the ratio of treatment to control-TN` has 1373 (87.5%) missing values	Missing
`the ratio of treatment to control-NH3` has 1369 (87.2%) missing values	Missing
`the ratio of treatment to control-N2O` has 1471 (93.7%) missing values	Missing
`the ratio of treatment to control-CH4` has 1501 (95.6%) missing values	Missing
`Scale` has 581 (37.0%) missing values	Missing
`Time Period` is an unsupported type, check if it needs cleaning or further analysis	Unsupported
`通风速率（L min-1 kg DW）` is an unsupported type, check if it needs cleaning or further analysis	Unsupported

Reproduction

Analysis started	2024-04-09 07:36:39.483930
Analysis finished	2024-04-09 07:37:15.752142
Duration	36.27 seconds
Software version	pandas-profiling v3.6.6
Download configuration	config.json

id
Real number (ℝ)

Distinct	434
Distinct (%)	27.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	200.26178

Minimum	1
Maximum	436
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	12.4 KiB

Quantile statistics

Minimum	1
5-th percentile	24
Q1	100
median	171.5
Q3	318
95-th percentile	422.55
Maximum	436
Range	435
Interquartile range (IQR)	218

Descriptive statistics

Standard deviation	127.11867
Coefficient of variation (CV)	0.63476249
Kurtosis	-1.0989291
Mean	200.26178
Median Absolute Deviation (MAD)	99.5
Skewness	0.32080339
Sum	314411
Variance	16159.156
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
119	24	1.5%
135	24	1.5%
173	21	1.3%
164	18	1.1%
159	18	1.1%
435	17	1.1%
334	16	1.0%
28	16	1.0%
39	16	1.0%
376	15	1.0%
Other values (424)	1385	88.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1	4	0.3%
2	4	0.3%
3	4	0.3%
4	4	0.3%
5	2	0.1%
6	3	0.2%
7	3	0.2%
8	2	0.1%
9	3	0.2%
10	4	0.3%

Value	Count	Frequency (%)
436	4	0.3%
435	17	1.1%
434	3	0.2%
433	3	0.2%
432	4	0.3%
431	5	0.3%
430	9	0.6%
429	2	0.1%
428	2	0.1%
427	3	0.2%

title
Categorical

HIGH CARDINALITY MISSING

Distinct	257
Distinct (%)	27.3%
Missing	628
Missing (%)	40.0%
Memory size	12.4 KiB

Nitrogen, carbon, and dry matter losses during composting of livestock manure with two bulking agents as affected by co-amendments of phosphogypsum and zeolite	27
Biochar combined with gypsum reduces both nitrogen and carbon losses during agricultural waste composting and enhances overall compost quality by regulating microbial activities and functions	24
Nitrogen loss in chicken litter compost as affected by carbon to nitrogen ratio and turning frequency	21
Effect of CN ratio, aeration rate and moisture content on ammonia and greenhouse gas emission during the composting	18
不同堆肥条件对堆肥过程中碳素损失及腐殖质形成的影响研究	18
Other values (252)	834

Length

Max length	284
Median length	191
Mean length	98.228238
Min length	15

Characters and Unicode

Total characters	92531
Distinct characters	287
Distinct categories	12 ?
Distinct scripts	3 ?
Distinct blocks	4 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	102 ?
Unique (%)	10.8%

Sample

1st row	The co-addition of biochar and manganese ore promotes nitrous oxide reduction but favors methane emission in sewage sludge composting
2nd row	The co-addition of biochar and manganese ore promotes nitrous oxide reduction but favors methane emission in sewage sludge composting
3rd row	The co-addition of biochar and manganese ore promotes nitrous oxide reduction but favors methane emission in sewage sludge composting
4th row	The co-addition of biochar and manganese ore promotes nitrous oxide reduction but favors methane emission in sewage sludge composting
5th row	The effect of carbonate and biochar on carbon and nitrogen losses during composting

Common Values

Value	Count	Frequency (%)
Nitrogen, carbon, and dry matter losses during composting of livestock manure with two bulking agents as affected by co-amendments of phosphogypsum and zeolite	27	1.7%
Biochar combined with gypsum reduces both nitrogen and carbon losses during agricultural waste composting and enhances overall compost quality by regulating microbial activities and functions	24	1.5%
Nitrogen loss in chicken litter compost as affected by carbon to nitrogen ratio and turning frequency	21	1.3%
Effect of CN ratio, aeration rate and moisture content on ammonia and greenhouse gas emission during the composting	18	1.1%
不同堆肥条件对堆肥过程中碳素损失及腐殖质形成的影响研究	18	1.1%
Effect of aeration rate, CN ratio and moisture content on the stability and maturity of compost	18	1.1%
Composting of solids separated from anaerobically digested animal manure: Effect of different bulking agents and mixing ratios on emissions of greenhouse gases and ammonia	17	1.1%
碳源调控对污泥堆肥过程氮素损失的影响及其作用机制	17	1.1%
Potential of aeration flow rate and bio-char addition to reduce greenhouse gas and ammonia emissions during manure composting	13	0.8%
Ammonia emissions and biodegradation of organic carbon during sewage sludge composting with different extra carbon sources	12	0.8%
Other values (247)	757	48.2%
(Missing)	628	40.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
of	946	7.4%
and	933	7.3%
composting	584	4.6%
during	410	3.2%
on	322	2.5%
manure	296	2.3%
the	275	2.2%
emissions	236	1.8%
nitrogen	213	1.7%
greenhouse	181	1.4%
Other values (988)	8378	65.6%

Most occurring characters

Value	Count	Frequency (%)
	11831	12.8%
o	7092	7.7%
n	6590	7.1%
e	6497	7.0%
i	6016	6.5%
a	5676	6.1%
t	5432	5.9%
s	5231	5.7%
r	4113	4.4%
m	3074	3.3%
Other values (277)	30979	33.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	70892	76.6%
Space Separator	11889	12.8%
Other Letter	5043	5.5%
Uppercase Letter	2380	2.6%
Other Punctuation	1234	1.3%
Decimal Number	673	0.7%
Dash Punctuation	272	0.3%
Close Punctuation	65	0.1%
Open Punctuation	65	0.1%
Initial Punctuation	7	< 0.1%
Other values (2)	11	< 0.1%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
堆	269	5.3%
肥	227	4.5%
的	168	3.3%
对	153	3.0%
气	145	2.9%
响	141	2.8%
影	141	2.8%
排	120	2.4%
放	118	2.3%
过	117	2.3%
Other values (189)	3444	68.3%

Lowercase Letter

Value	Count	Frequency (%)
o	7092	10.0%
n	6590	9.3%
e	6497	9.2%
i	6016	8.5%
a	5676	8.0%
t	5432	7.7%
s	5231	7.4%
r	4113	5.8%
m	3074	4.3%
d	2805	4.0%
Other values (21)	18366	25.9%

Uppercase Letter

Value	Count	Frequency (%)
C	349	14.7%
N	303	12.7%
E	280	11.8%
H	123	5.2%
A	119	5.0%
S	112	4.7%
T	105	4.4%
G	103	4.3%
I	100	4.2%
M	96	4.0%
Other values (16)	690	29.0%

Decimal Number

Value	Count	Frequency (%)
2	135	20.1%
3	114	16.9%
1	96	14.3%
0	87	12.9%
4	68	10.1%
9	52	7.7%
5	41	6.1%
6	33	4.9%
7	30	4.5%
8	17	2.5%

Other Punctuation

Value	Count	Frequency (%)
,	640	51.9%
.	474	38.4%
:	75	6.1%
、	28	2.3%
/	17	1.4%

Dash Punctuation

Value	Count	Frequency (%)
-	220	80.9%
–	46	16.9%
—	6	2.2%

Other Number

Value	Count	Frequency (%)
₂	2	50.0%
₃	1	25.0%
₄	1	25.0%

Space Separator

Value	Count	Frequency (%)
	11831	99.5%
	58	0.5%

Close Punctuation

Value	Count	Frequency (%)
)	63	96.9%
）	2	3.1%

Open Punctuation

Value	Count	Frequency (%)
(	63	96.9%
（	2	3.1%

Initial Punctuation

Value	Count	Frequency (%)
“	6	85.7%
‘	1	14.3%

Final Punctuation

Value	Count	Frequency (%)
”	6	85.7%
’	1	14.3%

Most occurring scripts

Value	Count	Frequency (%)
Latin	73272	79.2%
Common	14216	15.4%
Han	5043	5.5%

Most frequent character per script

Han

Value	Count	Frequency (%)
堆	269	5.3%
肥	227	4.5%
的	168	3.3%
对	153	3.0%
气	145	2.9%
响	141	2.8%
影	141	2.8%
排	120	2.4%
放	118	2.3%
过	117	2.3%
Other values (189)	3444	68.3%

Latin

Value	Count	Frequency (%)
o	7092	9.7%
n	6590	9.0%
e	6497	8.9%
i	6016	8.2%
a	5676	7.7%
t	5432	7.4%
s	5231	7.1%
r	4113	5.6%
m	3074	4.2%
d	2805	3.8%
Other values (47)	20746	28.3%

Common

Value	Count	Frequency (%)
	11831	83.2%
,	640	4.5%
.	474	3.3%
-	220	1.5%
2	135	0.9%
3	114	0.8%
1	96	0.7%
0	87	0.6%
:	75	0.5%
4	68	0.5%
Other values (21)	476	3.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	87310	94.4%
CJK	5043	5.5%
None	112	0.1%
Punctuation	66	0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	11831	13.6%
o	7092	8.1%
n	6590	7.5%
e	6497	7.4%
i	6016	6.9%
a	5676	6.5%
t	5432	6.2%
s	5231	6.0%
r	4113	4.7%
m	3074	3.5%
Other values (60)	25758	29.5%

CJK

Value	Count	Frequency (%)
堆	269	5.3%
肥	227	4.5%
的	168	3.3%
对	153	3.0%
气	145	2.9%
响	141	2.8%
影	141	2.8%
排	120	2.4%
放	118	2.3%
过	117	2.3%
Other values (189)	3444	68.3%

None

Value	Count	Frequency (%)
	58	51.8%
、	28	25.0%
á	6	5.4%
ó	5	4.5%
ö	3	2.7%
ü	3	2.7%
）	2	1.8%
（	2	1.8%
₂	2	1.8%
₃	1	0.9%
Other values (2)	2	1.8%

Punctuation

Value	Count	Frequency (%)
–	46	69.7%
“	6	9.1%
”	6	9.1%
—	6	9.1%
’	1	1.5%
‘	1	1.5%

author
Categorical

HIGH CARDINALITY MISSING

Distinct	267
Distinct (%)	24.0%
Missing	458
Missing (%)	29.2%
Memory size	12.4 KiB

Qu et al., 2020	24
Lim et al., 2017	24
Ogunwande et al., 2008	21
Guo et al., 2012	18
Jiang et al., 2011	18
Other values (262)	1007

Length

Max length	39
Median length	31
Mean length	20.044964
Min length	8

Characters and Unicode

Total characters	22290
Distinct characters	70
Distinct categories	6 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	33 ?
Unique (%)	3.0%

Sample

1st row	Limei Ren et al.,2010
2nd row	Limei Ren et al.,2010
3rd row	Limei Ren et al.,2010
4th row	Limei Ren et al.,2010
5th row	Khalil Tubail et al.,2008

Common Values

Value	Count	Frequency (%)
Qu et al., 2020	24	1.5%
Lim et al., 2017	24	1.5%
Ogunwande et al., 2008	21	1.3%
Guo et al., 2012	18	1.1%
Jiang et al., 2011	18	1.1%
Lu, 2007	16	1.0%
Leimei Ren et al.,2009	16	1.0%
M. Kithome, J. W. Paul et al.,1999	16	1.0%
Rincón et al. 2019a	15	1.0%
Xiaofeng Lin et al.,2008	13	0.8%
Other values (257)	931	59.3%
(Missing)	458	29.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
et	1024	23.2%
al	607	13.8%
jiang	90	2.0%
al.,2017	78	1.8%
2014	71	1.6%
2017	71	1.6%
2011	66	1.5%
2018	58	1.3%
li	53	1.2%
al.,2016	47	1.1%
Other values (266)	2241	50.9%

Most occurring characters

Value	Count	Frequency (%)
	3304	14.8%
a	1998	9.0%
e	1516	6.8%
0	1397	6.3%
2	1234	5.5%
l	1226	5.5%
t	1148	5.2%
.	1112	5.0%
,	977	4.4%
1	943	4.2%
Other values (60)	7435	33.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	10699	48.0%
Decimal Number	4452	20.0%
Space Separator	3304	14.8%
Other Punctuation	2089	9.4%
Uppercase Letter	1709	7.7%
Dash Punctuation	37	0.2%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	1998	18.7%
e	1516	14.2%
l	1226	11.5%
t	1148	10.7%
n	902	8.4%
i	747	7.0%
u	574	5.4%
g	447	4.2%
o	383	3.6%
h	352	3.3%
Other values (20)	1406	13.1%

Uppercase Letter

Value	Count	Frequency (%)
L	191	11.2%
J	175	10.2%
Y	128	7.5%
C	106	6.2%
S	106	6.2%
K	97	5.7%
M	95	5.6%
H	87	5.1%
W	85	5.0%
A	78	4.6%
Other values (16)	561	32.8%

Decimal Number

Value	Count	Frequency (%)
0	1397	31.4%
2	1234	27.7%
1	943	21.2%
7	176	4.0%
8	163	3.7%
9	153	3.4%
6	125	2.8%
5	112	2.5%
4	100	2.2%
3	49	1.1%

Other Punctuation

Value	Count	Frequency (%)
.	1112	53.2%
,	977	46.8%

Space Separator

Value	Count	Frequency (%)
	3304	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	37	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	12408	55.7%
Common	9882	44.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	1998	16.1%
e	1516	12.2%
l	1226	9.9%
t	1148	9.3%
n	902	7.3%
i	747	6.0%
u	574	4.6%
g	447	3.6%
o	383	3.1%
h	352	2.8%
Other values (46)	3115	25.1%

Common

Value	Count	Frequency (%)
	3304	33.4%
0	1397	14.1%
2	1234	12.5%
.	1112	11.3%
,	977	9.9%
1	943	9.5%
7	176	1.8%
8	163	1.6%
9	153	1.5%
6	125	1.3%
Other values (4)	298	3.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	22243	99.8%
None	47	0.2%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
	3304	14.9%
a	1998	9.0%
e	1516	6.8%
0	1397	6.3%
2	1234	5.5%
l	1226	5.5%
t	1148	5.2%
.	1112	5.0%
,	977	4.4%
1	943	4.2%
Other values (56)	7388	33.2%

None

Value	Count	Frequency (%)
ó	20	42.6%
ñ	17	36.2%
á	7	14.9%
í	3	6.4%

location
Categorical

HIGH CARDINALITY MISSING

Distinct	102
Distinct (%)	9.4%
Missing	486
Missing (%)	31.0%
Memory size	12.4 KiB

China	320
Europe	72
Canada	53
Asia	48
中国北京	44
Other values (97)	547

Length

Max length	49
Median length	28
Mean length	6.1291513
Min length	2

Characters and Unicode

Total characters	6644
Distinct characters	141
Distinct categories	5 ?
Distinct scripts	3 ?
Distinct blocks	3 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	25 ?
Unique (%)	2.3%

Sample

1st row	China
2nd row	China
3rd row	China
4th row	China
5th row	US

Common Values

Value	Count	Frequency (%)
China	320	20.4%
Europe	72	4.6%
Canada	53	3.4%
Asia	48	3.1%
中国北京	44	2.8%
Japan	36	2.3%
中国/北京	31	2.0%
US	29	1.8%
中国	27	1.7%
中国哈尔滨	26	1.7%
Other values (92)	398	25.4%
(Missing)	486	31.0%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
china	320	28.1%
europe	72	6.3%
中国北京	59	5.2%
canada	57	5.0%
asia	48	4.2%
japan	36	3.2%
中国/北京	35	3.1%
us	29	2.6%
中国	27	2.4%
中国哈尔滨	26	2.3%
Other values (97)	428	37.6%

Most occurring characters

Value	Count	Frequency (%)
a	816	12.3%
n	562	8.5%
i	447	6.7%
C	377	5.7%
h	375	5.6%
中	344	5.2%
国	340	5.1%
/	236	3.6%
r	200	3.0%
e	193	2.9%
Other values (131)	2754	41.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	3448	51.9%
Other Letter	1950	29.3%
Uppercase Letter	900	13.5%
Other Punctuation	258	3.9%
Space Separator	88	1.3%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
中	344	17.6%
国	340	17.4%
京	148	7.6%
北	140	7.2%
南	65	3.3%
江	53	2.7%
滨	52	2.7%
哈	52	2.7%
尔	52	2.7%
州	35	1.8%
Other values (86)	669	34.3%

Lowercase Letter

Value	Count	Frequency (%)
a	816	23.7%
n	562	16.3%
i	447	13.0%
h	375	10.9%
r	200	5.8%
e	193	5.6%
o	151	4.4%
p	132	3.8%
u	108	3.1%
d	105	3.0%
Other values (10)	359	10.4%

Uppercase Letter

Value	Count	Frequency (%)
C	377	41.9%
A	91	10.1%
E	88	9.8%
S	80	8.9%
U	62	6.9%
J	48	5.3%
D	40	4.4%
K	28	3.1%
F	17	1.9%
N	16	1.8%
Other values (9)	53	5.9%

Other Punctuation

Value	Count	Frequency (%)
/	236	91.5%
.	19	7.4%
'	2	0.8%
,	1	0.4%

Space Separator

Value	Count	Frequency (%)
	86	97.7%
	2	2.3%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4348	65.4%
Han	1950	29.3%
Common	346	5.2%

Most frequent character per script

Han

Value	Count	Frequency (%)
中	344	17.6%
国	340	17.4%
京	148	7.6%
北	140	7.2%
南	65	3.3%
江	53	2.7%
滨	52	2.7%
哈	52	2.7%
尔	52	2.7%
州	35	1.8%
Other values (86)	669	34.3%

Latin

Value	Count	Frequency (%)
a	816	18.8%
n	562	12.9%
i	447	10.3%
C	377	8.7%
h	375	8.6%
r	200	4.6%
e	193	4.4%
o	151	3.5%
p	132	3.0%
u	108	2.5%
Other values (29)	987	22.7%

Common

Value	Count	Frequency (%)
/	236	68.2%
	86	24.9%
.	19	5.5%
	2	0.6%
'	2	0.6%
,	1	0.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	4692	70.6%
CJK	1950	29.3%
None	2	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	816	17.4%
n	562	12.0%
i	447	9.5%
C	377	8.0%
h	375	8.0%
/	236	5.0%
r	200	4.3%
e	193	4.1%
o	151	3.2%
p	132	2.8%
Other values (34)	1203	25.6%

CJK

Value	Count	Frequency (%)
中	344	17.6%
国	340	17.4%
京	148	7.6%
北	140	7.2%
南	65	3.3%
江	53	2.7%
滨	52	2.7%
哈	52	2.7%
尔	52	2.7%
州	35	1.8%
Other values (86)	669	34.3%

None

Value	Count	Frequency (%)
	2	100.0%

Journal
Categorical

HIGH CARDINALITY MISSING

Distinct	68
Distinct (%)	8.0%
Missing	718
Missing (%)	45.7%
Memory size	12.4 KiB

Bioresource Technology	208
Waste Management	67
Journal of Agro-Environment Science (in Chinese)	51
Ecological Engineering	41
Journal of Environmental Quality	37
Other values (63)	448

Length

Max length	75
Median length	60
Mean length	28.825117
Min length	10

Characters and Unicode

Total characters	24559
Distinct characters	62
Distinct categories	8 ?
Distinct scripts	2 ?
Distinct blocks	2 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.1%

Sample

1st row	waste management
2nd row	waste management
3rd row	waste management
4th row	waste management
5th row	compost science & utilization

Common Values

Value	Count	Frequency (%)
Bioresource Technology	208	13.2%
Waste Management	67	4.3%
Journal of Agro-Environment Science (in Chinese)	51	3.2%
Ecological Engineering	41	2.6%
Journal of Environmental Quality	37	2.4%
Chemosphere	35	2.2%
Journal of Environmental Sciences	26	1.7%
Journal of Cleaner Production	23	1.5%
Environmental Technology	21	1.3%
waste management	21	1.3%
Other values (58)	322	20.5%
(Missing)	718	45.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
of	286	10.0%
technology	247	8.7%
journal	237	8.3%
bioresource	208	7.3%
environmental	171	6.0%
chinese	162	5.7%
science	137	4.8%
management	132	4.6%
waste	116	4.1%
and	76	2.7%
Other values (98)	1083	37.9%

Most occurring characters

Value	Count	Frequency (%)
e	2678	10.9%
n	2603	10.6%
o	2289	9.3%
	2009	8.2%
i	1620	6.6%
r	1386	5.6%
a	1293	5.3%
c	1178	4.8%
l	1112	4.5%
t	968	3.9%
Other values (52)	7423	30.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	19733	80.3%
Uppercase Letter	2419	9.8%
Space Separator	2013	8.2%
Close Punctuation	124	0.5%
Open Punctuation	124	0.5%
Other Punctuation	85	0.3%
Dash Punctuation	57	0.2%
Decimal Number	4	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	2678	13.6%
n	2603	13.2%
o	2289	11.6%
i	1620	8.2%
r	1386	7.0%
a	1293	6.6%
c	1178	6.0%
l	1112	5.6%
t	968	4.9%
s	833	4.2%
Other values (14)	3773	19.1%

Uppercase Letter

Value	Count	Frequency (%)
E	424	17.5%
T	276	11.4%
C	263	10.9%
B	260	10.7%
J	253	10.5%
S	241	10.0%
A	148	6.1%
M	138	5.7%
W	97	4.0%
P	85	3.5%
Other values (14)	234	9.7%

Other Punctuation

Value	Count	Frequency (%)
&	38	44.7%
.	23	27.1%
,	20	23.5%
＆	2	2.4%
"	2	2.4%

Decimal Number

Value	Count	Frequency (%)
2	1	25.0%
0	1	25.0%
1	1	25.0%
5	1	25.0%

Space Separator

Value	Count	Frequency (%)
	2009	99.8%
	4	0.2%

Close Punctuation

Value	Count	Frequency (%)
)	124	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	124	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	57	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	22152	90.2%
Common	2407	9.8%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	2678	12.1%
n	2603	11.8%
o	2289	10.3%
i	1620	7.3%
r	1386	6.3%
a	1293	5.8%
c	1178	5.3%
l	1112	5.0%
t	968	4.4%
s	833	3.8%
Other values (38)	6192	28.0%

Common

Value	Count	Frequency (%)
	2009	83.5%
)	124	5.2%
(	124	5.2%
-	57	2.4%
&	38	1.6%
.	23	1.0%
,	20	0.8%
	4	0.2%
＆	2	0.1%
"	2	0.1%
Other values (4)	4	0.2%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	24553	> 99.9%
None	6	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	2678	10.9%
n	2603	10.6%
o	2289	9.3%
	2009	8.2%
i	1620	6.6%
r	1386	5.6%
a	1293	5.3%
c	1178	4.8%
l	1112	4.5%
t	968	3.9%
Other values (50)	7417	30.2%

None

Value	Count	Frequency (%)
	4	66.7%
＆	2	33.3%

material_0
Categorical

Distinct	6
Distinct (%)	0.4%
Missing	126
Missing (%)	8.0%
Memory size	12.4 KiB

Manure	952
Sewage sludge	240
Food waste	115
Lignin	92
Digestate	43

Length

Max length	13
Median length	6
Mean length	7.5699446
Min length	5

Characters and Unicode

Total characters	10931
Distinct characters	21
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Manure
2nd row	Manure
3rd row	Manure
4th row	Manure
5th row	Manure

Common Values

Value	Count	Frequency (%)
Manure	952	60.6%
Sewage sludge	240	15.3%
Food waste	115	7.3%
Lignin	92	5.9%
Digestate	43	2.7%
Other	2	0.1%
(Missing)	126	8.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
manure	952	52.9%
sewage	240	13.3%
sludge	240	13.3%
food	115	6.4%
waste	115	6.4%
lignin	92	5.1%
digestate	43	2.4%
other	2	0.1%

Most occurring characters

Value	Count	Frequency (%)
e	1875	17.2%
a	1350	12.4%
u	1192	10.9%
n	1136	10.4%
r	954	8.7%
M	952	8.7%
g	615	5.6%
s	398	3.6%
w	355	3.2%
	355	3.2%
Other values (11)	1749	16.0%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	9132	83.5%
Uppercase Letter	1444	13.2%
Space Separator	355	3.2%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	1875	20.5%
a	1350	14.8%
u	1192	13.1%
n	1136	12.4%
r	954	10.4%
g	615	6.7%
s	398	4.4%
w	355	3.9%
d	355	3.9%
l	240	2.6%
Other values (4)	662	7.2%

Uppercase Letter

Value	Count	Frequency (%)
M	952	65.9%
S	240	16.6%
F	115	8.0%
L	92	6.4%
D	43	3.0%
O	2	0.1%

Space Separator

Value	Count	Frequency (%)
	355	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	10576	96.8%
Common	355	3.2%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	1875	17.7%
a	1350	12.8%
u	1192	11.3%
n	1136	10.7%
r	954	9.0%
M	952	9.0%
g	615	5.8%
s	398	3.8%
w	355	3.4%
d	355	3.4%
Other values (10)	1394	13.2%

Common

Value	Count	Frequency (%)
	355	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	10931	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	1875	17.2%
a	1350	12.4%
u	1192	10.9%
n	1136	10.4%
r	954	8.7%
M	952	8.7%
g	615	5.6%
s	398	3.6%
w	355	3.2%
	355	3.2%
Other values (11)	1749	16.0%

material_1
Categorical

Distinct	7
Distinct (%)	0.7%
Missing	618
Missing (%)	39.4%
Memory size	12.4 KiB

Swine manure	440
Poultry manure	235
Cow manure	212
Manure	57
Horse manure	5
Other values (2)	3

Length

Max length	14
Median length	13
Mean length	11.685924
Min length	6

Characters and Unicode

Total characters	11125
Distinct characters	19
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	0.1%

Sample

1st row	Swine manure
2nd row	Swine manure
3rd row	Swine manure
4th row	Swine manure
5th row	Cow manure

Common Values

Value	Count	Frequency (%)
Swine manure	440	28.0%
Poultry manure	235	15.0%
Cow manure	212	13.5%
Manure	57	3.6%
Horse manure	5	0.3%
Human manure	2	0.1%
Manure	1	0.1%
(Missing)	618	39.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
manure	952	51.6%
swine	440	23.8%
poultry	235	12.7%
cow	212	11.5%
horse	5	0.3%
human	2	0.1%

Most occurring characters

Value	Count	Frequency (%)
e	1397	12.6%
n	1394	12.5%
r	1192	10.7%
u	1189	10.7%
a	954	8.6%
	897	8.1%
m	896	8.1%
w	652	5.9%
o	452	4.1%
S	440	4.0%
Other values (9)	1662	14.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	9276	83.4%
Uppercase Letter	952	8.6%
Space Separator	897	8.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	1397	15.1%
n	1394	15.0%
r	1192	12.9%
u	1189	12.8%
a	954	10.3%
m	896	9.7%
w	652	7.0%
o	452	4.9%
i	440	4.7%
l	235	2.5%
Other values (3)	475	5.1%

Uppercase Letter

Value	Count	Frequency (%)
S	440	46.2%
P	235	24.7%
C	212	22.3%
M	58	6.1%
H	7	0.7%

Space Separator

Value	Count	Frequency (%)
	897	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	10228	91.9%
Common	897	8.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	1397	13.7%
n	1394	13.6%
r	1192	11.7%
u	1189	11.6%
a	954	9.3%
m	896	8.8%
w	652	6.4%
o	452	4.4%
S	440	4.3%
i	440	4.3%
Other values (8)	1222	11.9%

Common

Value	Count	Frequency (%)
	897	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	11125	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	1397	12.6%
n	1394	12.5%
r	1192	10.7%
u	1189	10.7%
a	954	8.6%
	897	8.1%
m	896	8.1%
w	652	5.9%
o	452	4.1%
S	440	4.0%
Other values (9)	1662	14.9%

Excipients
Categorical

HIGH CARDINALITY MISSING

Distinct	139
Distinct (%)	17.1%
Missing	758
Missing (%)	48.3%
Memory size	12.4 KiB

玉米秸秆	96
小麦秸秆	46
Wheat straw	37
Sawdust	36
锯末	30
Other values (134)	567

Length

Max length	38
Median length	32
Mean length	8.4371921
Min length	2

Characters and Unicode

Total characters	6851
Distinct characters	130
Distinct categories	7 ?
Distinct scripts	3 ?
Distinct blocks	3 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	55 ?
Unique (%)	6.8%

Sample

1st row	Corn straw
2nd row	Corn straw
3rd row	Corn straw
4th row	Corn straw
5th row	Cereal chaff

Common Values

Value	Count	Frequency (%)
玉米秸秆	96	6.1%
小麦秸秆	46	2.9%
Wheat straw	37	2.4%
Sawdust	36	2.3%
锯末	30	1.9%
Cornstalk	27	1.7%
木屑	27	1.7%
稻草	27	1.7%
Plant straw	24	1.5%
蘑菇渣	21	1.3%
Other values (129)	441	28.1%
(Missing)	758	48.3%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
straw	126	10.1%
玉米秸秆	96	7.7%
sawdust	63	5.0%
corn	54	4.3%
小麦秸秆	52	4.2%
	45	3.6%
wheat	40	3.2%
manure	39	3.1%
stalks	37	3.0%
锯末	30	2.4%
Other values (142)	671	53.6%

Most occurring characters

Value	Count	Frequency (%)
a	550	8.0%
	491	7.2%
t	472	6.9%
s	449	6.6%
r	366	5.3%
e	353	5.2%
w	251	3.7%
o	227	3.3%
秸	223	3.3%
秆	223	3.3%
Other values (120)	3246	47.4%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	4054	59.2%
Other Letter	1666	24.3%
Space Separator	491	7.2%
Uppercase Letter	430	6.3%
Math Symbol	200	2.9%
Other Punctuation	9	0.1%
Decimal Number	1	< 0.1%

Most frequent character per category

Other Letter

Value	Count	Frequency (%)
秸	223	13.4%
秆	223	13.4%
米	113	6.8%
玉	103	6.2%
麦	80	4.8%
渣	71	4.3%
小	70	4.2%
稻	59	3.5%
屑	50	3.0%
锯	44	2.6%
Other values (75)	630	37.8%

Lowercase Letter

Value	Count	Frequency (%)
a	550	13.6%
t	472	11.6%
s	449	11.1%
r	366	9.0%
e	353	8.7%
w	251	6.2%
o	227	5.6%
n	216	5.3%
l	197	4.9%
u	190	4.7%
Other values (13)	783	19.3%

Uppercase Letter

Value	Count	Frequency (%)
S	119	27.7%
C	98	22.8%
P	51	11.9%
W	38	8.8%
M	34	7.9%
R	18	4.2%
B	17	4.0%
D	14	3.3%
G	9	2.1%
F	9	2.1%
Other values (6)	23	5.3%

Other Punctuation

Value	Count	Frequency (%)
,	4	44.4%
.	4	44.4%
、	1	11.1%

Space Separator

Value	Count	Frequency (%)
	491	100.0%

Math Symbol

Value	Count	Frequency (%)
+	200	100.0%

Decimal Number

Value	Count	Frequency (%)
4	1	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	4484	65.5%
Han	1666	24.3%
Common	701	10.2%

Most frequent character per script

Han

Value	Count	Frequency (%)
秸	223	13.4%
秆	223	13.4%
米	113	6.8%
玉	103	6.2%
麦	80	4.8%
渣	71	4.3%
小	70	4.2%
稻	59	3.5%
屑	50	3.0%
锯	44	2.6%
Other values (75)	630	37.8%

Latin

Value	Count	Frequency (%)
a	550	12.3%
t	472	10.5%
s	449	10.0%
r	366	8.2%
e	353	7.9%
w	251	5.6%
o	227	5.1%
n	216	4.8%
l	197	4.4%
u	190	4.2%
Other values (29)	1213	27.1%

Common

Value	Count	Frequency (%)
	491	70.0%
+	200	28.5%
,	4	0.6%
.	4	0.6%
、	1	0.1%
4	1	0.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	5184	75.7%
CJK	1666	24.3%
None	1	< 0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	550	10.6%
	491	9.5%
t	472	9.1%
s	449	8.7%
r	366	7.1%
e	353	6.8%
w	251	4.8%
o	227	4.4%
n	216	4.2%
+	200	3.9%
Other values (34)	1609	31.0%

CJK

Value	Count	Frequency (%)
秸	223	13.4%
秆	223	13.4%
米	113	6.8%
玉	103	6.2%
麦	80	4.8%
渣	71	4.3%
小	70	4.2%
稻	59	3.5%
屑	50	3.0%
锯	44	2.6%
Other values (75)	630	37.8%

None

Value	Count	Frequency (%)
、	1	100.0%

Additive Species
Categorical

Distinct	4
Distinct (%)	0.8%
Missing	1098
Missing (%)	69.9%
Memory size	12.4 KiB

Physical	286
Chemical	132
Biological	39
Mixture	15

Length

Max length	10
Median length	8
Mean length	8.1334746
Min length	7

Characters and Unicode

Total characters	3839
Distinct characters	19
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Chemical
2nd row	Chemical
3rd row	Chemical
4th row	Physical
5th row	Physical

Common Values

Value	Count	Frequency (%)
Physical	286	18.2%
Chemical	132	8.4%
Biological	39	2.5%
Mixture	15	1.0%
(Missing)	1098	69.9%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
physical	286	60.6%
chemical	132	28.0%
biological	39	8.3%
mixture	15	3.2%

Most occurring characters

Value	Count	Frequency (%)
i	511	13.3%
l	496	12.9%
c	457	11.9%
a	457	11.9%
h	418	10.9%
P	286	7.4%
y	286	7.4%
s	286	7.4%
e	147	3.8%
C	132	3.4%
Other values (9)	363	9.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	3367	87.7%
Uppercase Letter	472	12.3%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
i	511	15.2%
l	496	14.7%
c	457	13.6%
a	457	13.6%
h	418	12.4%
y	286	8.5%
s	286	8.5%
e	147	4.4%
m	132	3.9%
o	78	2.3%
Other values (5)	99	2.9%

Uppercase Letter

Value	Count	Frequency (%)
P	286	60.6%
C	132	28.0%
B	39	8.3%
M	15	3.2%

Most occurring scripts

Value	Count	Frequency (%)
Latin	3839	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
i	511	13.3%
l	496	12.9%
c	457	11.9%
a	457	11.9%
h	418	10.9%
P	286	7.4%
y	286	7.4%
s	286	7.4%
e	147	3.8%
C	132	3.4%
Other values (9)	363	9.5%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3839	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
i	511	13.3%
l	496	12.9%
c	457	11.9%
a	457	11.9%
h	418	10.9%
P	286	7.4%
y	286	7.4%
s	286	7.4%
e	147	3.8%
C	132	3.4%
Other values (9)	363	9.5%

Additive_1
Categorical

HIGH CARDINALITY MISSING

Distinct	124
Distinct (%)	26.3%
Missing	1098
Missing (%)	69.9%
Memory size	12.4 KiB

biochar	56
PO43- and Mg2+ salts	46
superphosphate	32
zeolite	31
Biochar	26
Other values (119)	281

Length

Max length	119
Median length	32
Mean length	13.436441
Min length	1

Characters and Unicode

Total characters	6342
Distinct characters	60
Distinct categories	10 ?
Distinct scripts	2 ?
Distinct blocks	3 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	66 ?
Unique (%)	14.0%

Sample

1st row	PO43- and Mg2+ salts
2nd row	PO43- and Mg2+ salts
3rd row	PO43- and Mg2+ salts
4th row	gypsum
5th row	gypsum

Common Values

Value	Count	Frequency (%)
biochar	56	3.6%
PO43- and Mg2+ salts	46	2.9%
superphosphate	32	2.0%
zeolite	31	2.0%
Biochar	26	1.7%
phosphogypsum	15	1.0%
gypsum	12	0.8%
Biochar	9	0.6%
clay	8	0.5%
microbiological agent	8	0.5%
Other values (114)	229	14.6%
(Missing)	1098	69.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
biochar	108	12.9%
and	67	8.0%
mg2	46	5.5%
salts	46	5.5%
po43	46	5.5%
superphosphate	40	4.8%
zeolite	34	4.0%
phosphogypsum	21	2.5%
gypsum	18	2.1%
clay	13	1.5%
Other values (140)	401	47.7%

Most occurring characters

Value	Count	Frequency (%)
a	564	8.9%
o	422	6.7%
	406	6.4%
i	405	6.4%
e	392	6.2%
s	363	5.7%
t	299	4.7%
r	294	4.6%
h	289	4.6%
p	260	4.1%
Other values (50)	2648	41.8%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	4893	77.2%
Uppercase Letter	558	8.8%
Space Separator	420	6.6%
Decimal Number	293	4.6%
Dash Punctuation	57	0.9%
Math Symbol	56	0.9%
Open Punctuation	23	0.4%
Close Punctuation	23	0.4%
Other Punctuation	17	0.3%
Connector Punctuation	2	< 0.1%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
a	564	11.5%
o	422	8.6%
i	405	8.3%
e	392	8.0%
s	363	7.4%
t	299	6.1%
r	294	6.0%
h	289	5.9%
p	260	5.3%
c	229	4.7%
Other values (15)	1376	28.1%

Uppercase Letter

Value	Count	Frequency (%)
O	121	21.7%
P	79	14.2%
M	62	11.1%
H	54	9.7%
B	54	9.7%
C	41	7.3%
S	32	5.7%
N	30	5.4%
T	22	3.9%
A	18	3.2%
Other values (8)	45	8.1%

Decimal Number

Value	Count	Frequency (%)
2	105	35.8%
4	96	32.8%
3	67	22.9%
1	9	3.1%
0	8	2.7%
5	7	2.4%
9	1	0.3%

Space Separator

Value	Count	Frequency (%)
	406	96.7%
	10	2.4%
	4	1.0%

Other Punctuation

Value	Count	Frequency (%)
,	16	94.1%
.	1	5.9%

Dash Punctuation

Value	Count	Frequency (%)
-	57	100.0%

Math Symbol

Value	Count	Frequency (%)
+	56	100.0%

Open Punctuation

Value	Count	Frequency (%)
(	23	100.0%

Close Punctuation

Value	Count	Frequency (%)
)	23	100.0%

Connector Punctuation

Value	Count	Frequency (%)
_	2	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	5451	86.0%
Common	891	14.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
a	564	10.3%
o	422	7.7%
i	405	7.4%
e	392	7.2%
s	363	6.7%
t	299	5.5%
r	294	5.4%
h	289	5.3%
p	260	4.8%
c	229	4.2%
Other values (33)	1934	35.5%

Common

Value	Count	Frequency (%)
	406	45.6%
2	105	11.8%
4	96	10.8%
3	67	7.5%
-	57	6.4%
+	56	6.3%
(	23	2.6%
)	23	2.6%
,	16	1.8%
	10	1.1%
Other values (7)	32	3.6%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	6328	99.8%
None	10	0.2%
Punctuation	4	0.1%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
a	564	8.9%
o	422	6.7%
	406	6.4%
i	405	6.4%
e	392	6.2%
s	363	5.7%
t	299	4.7%
r	294	4.6%
h	289	4.6%
p	260	4.1%
Other values (48)	2634	41.6%

None

Value	Count	Frequency (%)
	10	100.0%

Punctuation

Value	Count	Frequency (%)
	4	100.0%

Additive_2
Categorical

Distinct	10
Distinct (%)	41.7%
Missing	1546
Missing (%)	98.5%
Memory size	12.4 KiB

zeolite	6
DCD	4
Gypsum	4
Calcium-bontonite	3
Urea	2
Other values (5)	5

Length

Max length	19
Median length	16
Mean length	8.625
Min length	3

Characters and Unicode

Total characters	207
Distinct characters	31
Distinct categories	4 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	5 ?
Unique (%)	20.8%

Sample

1st row	activated charcoal
2nd row	Manganese ore
3rd row	Ferrous Sulfate
4th row	Bean dreg
5th row	Gypsum

Common Values

Value	Count	Frequency (%)
zeolite	6	0.4%
DCD	4	0.3%
Gypsum	4	0.3%
Calcium-bontonite	3	0.2%
Urea	2	0.1%
activated charcoal	1	0.1%
Ferrous Sulfate	1	0.1%
sheep manure	1	0.1%
Manganese ore	1	0.1%
Bean dreg	1	0.1%
(Missing)	1546	98.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
zeolite	6	20.7%
dcd	4	13.8%
gypsum	4	13.8%
calcium-bontonite	3	10.3%
urea	2	6.9%
activated	1	3.4%
charcoal	1	3.4%
ferrous	1	3.4%
sulfate	1	3.4%
sheep	1	3.4%
Other values (5)	5	17.2%

Most occurring characters

Value	Count	Frequency (%)
e	28	13.5%
o	15	7.2%
t	15	7.2%
a	14	6.8%
i	13	6.3%
l	11	5.3%
n	10	4.8%
u	10	4.8%
D	8	3.9%
	8	3.9%
Other values (21)	75	36.2%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	171	82.6%
Uppercase Letter	25	12.1%
Space Separator	8	3.9%
Dash Punctuation	3	1.4%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
e	28	16.4%
o	15	8.8%
t	15	8.8%
a	14	8.2%
i	13	7.6%
l	11	6.4%
n	10	5.8%
u	10	5.8%
r	8	4.7%
m	8	4.7%
Other values (11)	39	22.8%

Uppercase Letter

Value	Count	Frequency (%)
D	8	32.0%
C	7	28.0%
G	4	16.0%
U	2	8.0%
F	1	4.0%
S	1	4.0%
M	1	4.0%
B	1	4.0%

Space Separator

Value	Count	Frequency (%)
	8	100.0%

Dash Punctuation

Value	Count	Frequency (%)
-	3	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	196	94.7%
Common	11	5.3%

Most frequent character per script

Latin

Value	Count	Frequency (%)
e	28	14.3%
o	15	7.7%
t	15	7.7%
a	14	7.1%
i	13	6.6%
l	11	5.6%
n	10	5.1%
u	10	5.1%
D	8	4.1%
r	8	4.1%
Other values (19)	64	32.7%

Common

Value	Count	Frequency (%)
	8	72.7%
-	3	27.3%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	207	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
e	28	13.5%
o	15	7.2%
t	15	7.2%
a	14	6.8%
i	13	6.3%
l	11	5.3%
n	10	4.8%
u	10	4.8%
D	8	3.9%
	8	3.9%
Other values (21)	75	36.2%

Application Rate (%)
Real number (ℝ)

Distinct	107
Distinct (%)	34.7%
Missing	1262
Missing (%)	80.4%
Infinite	0
Infinite (%)	0.0%
Mean	13.972546

Minimum	0.002
Maximum	54
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	12.4 KiB

Quantile statistics

Minimum	0.002
5-th percentile	1
Q1	5.15
median	10
Q3	20
95-th percentile	33
Maximum	54
Range	53.998
Interquartile range (IQR)	14.85

Descriptive statistics

Standard deviation	10.7479
Coefficient of variation (CV)	0.76921555
Kurtosis	1.7477216
Mean	13.972546
Median Absolute Deviation (MAD)	5.3
Skewness	1.2370117
Sum	4303.5443
Variance	115.51735
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
10	46	2.9%
5	25	1.6%
25	16	1.0%
20	16	1.0%
15	14	0.9%
23	12	0.8%
1	10	0.6%
6	8	0.5%
14	7	0.4%
33	7	0.4%
Other values (97)	147	9.4%
(Missing)	1262	80.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.002	1	0.1%
0.25	3	0.2%
0.3465	1	0.1%
0.38475	1	0.1%
0.4	3	0.2%
0.42075	1	0.1%
0.6	1	0.1%
0.88	1	0.1%
1	10	0.6%
1.5	1	0.1%

Value	Count	Frequency (%)
54	1	0.1%
52.6	1	0.1%
51	1	0.1%
50	3	0.2%
47	1	0.1%
42	1	0.1%
40	1	0.1%
38.9	2	0.1%
38	1	0.1%
37.8	2	0.1%

initial moisture content(%)
Real number (ℝ)

Distinct	322
Distinct (%)	30.3%
Missing	509
Missing (%)	32.4%
Infinite	0
Infinite (%)	0.0%
Mean	65.478364

Minimum	40
Maximum	89.8
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	12.4 KiB

Quantile statistics

Minimum	40
5-th percentile	52.8
Q1	60
median	65
Q3	70
95-th percentile	81.08
Maximum	89.8
Range	49.8
Interquartile range (IQR)	10

Descriptive statistics

Standard deviation	8.1561721
Coefficient of variation (CV)	0.12456286
Kurtosis	0.50852021
Mean	65.478364
Median Absolute Deviation (MAD)	5
Skewness	0.30310652
Sum	69472.544
Variance	66.523144
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
60	124	7.9%
65	117	7.5%
70	36	2.3%
55	24	1.5%
63	19	1.2%
72.1	14	0.9%
61	13	0.8%
75	12	0.8%
66	12	0.8%
64	12	0.8%
Other values (312)	678	43.2%
(Missing)	509	32.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
40	2	0.1%
43.6	1	0.1%
43.61	1	0.1%
44	1	0.1%
45	5	0.3%
45.32	1	0.1%
46.3	1	0.1%
46.7	1	0.1%
46.9	2	0.1%
47.5	3	0.2%

Value	Count	Frequency (%)
89.8	1	0.1%
88.5	7	0.4%
86	1	0.1%
85.5	1	0.1%
85.33	2	0.1%
85	3	0.2%
84.89	1	0.1%
84.7	1	0.1%
84.66	2	0.1%
84.3	5	0.3%

initial pH
Real number (ℝ)

Distinct	278
Distinct (%)	28.5%
Missing	596
Missing (%)	38.0%
Infinite	0
Infinite (%)	0.0%
Mean	7.4673292

Minimum	3.51
Maximum	10.7
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	12.4 KiB

Quantile statistics

Minimum	3.51
5-th percentile	5.693
Q1	6.9
median	7.6
Q3	8.17
95-th percentile	8.8
Maximum	10.7
Range	7.19
Interquartile range (IQR)	1.27

Descriptive statistics

Standard deviation	0.97858746
Coefficient of variation (CV)	0.13104919
Kurtosis	0.48184693
Mean	7.4673292
Median Absolute Deviation (MAD)	0.61
Skewness	-0.52683973
Sum	7273.1786
Variance	0.95763342
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
8.6	46	2.9%
7.6	29	1.8%
7.8	28	1.8%
6.5	22	1.4%
8.3	21	1.3%
8.2	21	1.3%
7.1	20	1.3%
6.9	19	1.2%
8.4	19	1.2%
8	19	1.2%
Other values (268)	730	46.5%
(Missing)	596	38.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
3.51	1	0.1%
4.28	2	0.1%
4.42231	1	0.1%
4.43	2	0.1%
4.45	1	0.1%
4.8	1	0.1%
4.81275	1	0.1%
4.9	1	0.1%
4.92	1	0.1%
5	3	0.2%

Value	Count	Frequency (%)
10.7	1	0.1%
10.32	2	0.1%
10	1	0.1%
9.8	2	0.1%
9.6	1	0.1%
9.4	1	0.1%
9.35	1	0.1%
9.33	1	0.1%
9.2	2	0.1%
9.19	1	0.1%

initial TN(%)
Real number (ℝ)

Distinct	280
Distinct (%)	48.4%
Missing	992
Missing (%)	63.2%
Infinite	0
Infinite (%)	0.0%
Mean	2.5465543

Minimum	0.37
Maximum	14.56
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	12.4 KiB

Quantile statistics

Minimum	0.37
5-th percentile	0.9185
Q1	1.46
median	2.02
Q3	2.7375
95-th percentile	7.5
Maximum	14.56
Range	14.19
Interquartile range (IQR)	1.2775

Descriptive statistics

Standard deviation	1.9951525
Coefficient of variation (CV)	0.78347143
Kurtosis	11.613934
Mean	2.5465543
Median Absolute Deviation (MAD)	0.62
Skewness	3.0938075
Sum	1471.9084
Variance	3.9806337
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1.9	19	1.2%
3.103822807	18	1.1%
1.4	14	0.9%
2.4	13	0.8%
2.1	13	0.8%
1.7	10	0.6%
1.8	10	0.6%
1.79	9	0.6%
1.78	8	0.5%
2.04	7	0.4%
Other values (270)	457	29.1%
(Missing)	992	63.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.37	1	0.1%
0.68	2	0.1%
0.69	3	0.2%
0.7	2	0.1%
0.723	1	0.1%
0.77	1	0.1%
0.782	1	0.1%
0.794	1	0.1%
0.8	2	0.1%
0.807	1	0.1%

Value	Count	Frequency (%)
14.56	1	0.1%
14.2	2	0.1%
13.4	1	0.1%
13.1	1	0.1%
11.58	1	0.1%
11.12	1	0.1%
10.4	1	0.1%
10.27	1	0.1%
10	1	0.1%
9.79	1	0.1%

initial TC(%)
Real number (ℝ)

Distinct	332
Distinct (%)	59.5%
Missing	1012
Missing (%)	64.5%
Infinite	0
Infinite (%)	0.0%
Mean	50.863042

Minimum	1.45
Maximum	197
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	12.4 KiB

Quantile statistics

Minimum	1.45
5-th percentile	24.8985
Q1	35.9
median	40.7
Q3	49
95-th percentile	135.15
Maximum	197
Range	195.55
Interquartile range (IQR)	13.1

Descriptive statistics

Standard deviation	33.106559
Coefficient of variation (CV)	0.65089617
Kurtosis	6.9225999
Mean	50.863042
Median Absolute Deviation (MAD)	6.3
Skewness	2.6280395
Sum	28381.577
Variance	1096.0442
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
61.57221742	18	1.1%
38	9	0.6%
72.33	8	0.5%
37.48	7	0.4%
37.3	7	0.4%
40	7	0.4%
36.9	7	0.4%
78.27	7	0.4%
48.99	7	0.4%
35.2	7	0.4%
Other values (322)	474	30.2%
(Missing)	1012	64.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1.45	3	0.2%
5.8	1	0.1%
5.85	1	0.1%
6	1	0.1%
6.35	1	0.1%
19.14	1	0.1%
19.152	1	0.1%
19.3	1	0.1%
20.2	1	0.1%
21.8	1	0.1%

Value	Count	Frequency (%)
197	1	0.1%
196.75	2	0.1%
193.8	1	0.1%
192.61	1	0.1%
185	1	0.1%
180.67	1	0.1%
180.05	1	0.1%
178.23	1	0.1%
177.9	1	0.1%
174.91	1	0.1%

initial CN(%)
Real number (ℝ)

Distinct	477
Distinct (%)	42.7%
Missing	453
Missing (%)	28.9%
Infinite	0
Infinite (%)	0.0%
Mean	21.51954

Minimum	1.1
Maximum	53.73494
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	12.4 KiB

Quantile statistics

Minimum	1.1
5-th percentile	9.715
Q1	15.508257
median	20
Q3	25.21
95-th percentile	37.516812
Maximum	53.73494
Range	52.63494
Interquartile range (IQR)	9.7017431

Descriptive statistics

Standard deviation	8.7820421
Coefficient of variation (CV)	0.40809619
Kurtosis	1.4460812
Mean	21.51954
Median Absolute Deviation (MAD)	5
Skewness	0.95790181
Sum	24037.326
Variance	77.124263
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
25	76	4.8%
30	59	3.8%
20	42	2.7%
15	32	2.0%
18	24	1.5%
21	16	1.0%
17.8	14	0.9%
19	13	0.8%
18.4	12	0.8%
29	12	0.8%
Other values (467)	817	52.0%
(Missing)	453	28.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
1.1	1	0.1%
2.536745928	1	0.1%
2.901592789	1	0.1%
4.43	3	0.2%
4.89	1	0.1%
4.916910084	1	0.1%
5.22	1	0.1%
5.4	1	0.1%
6.1	9	0.6%
6.15	1	0.1%

Value	Count	Frequency (%)
53.73493976	1	0.1%
53.69565217	1	0.1%
53.37662338	1	0.1%
53.00827305	1	0.1%
52.88659794	2	0.1%
52.0212766	1	0.1%
51.70992366	1	0.1%
51.54255319	1	0.1%
51.5	1	0.1%
51.20879121	1	0.1%

TN loss (%)
Real number (ℝ)

Distinct	395
Distinct (%)	70.2%
Missing	1007
Missing (%)	64.1%
Infinite	0
Infinite (%)	0.0%
Mean	28.950867

Minimum	0.2
Maximum	90.5
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	12.4 KiB

Quantile statistics

Minimum	0.2
5-th percentile	2.73
Q1	15.65
median	26.530612
Q3	39.7
95-th percentile	63
Maximum	90.5
Range	90.3
Interquartile range (IQR)	24.05

Descriptive statistics

Standard deviation	18.936026
Coefficient of variation (CV)	0.65407459
Kurtosis	1.1344181
Mean	28.950867
Median Absolute Deviation (MAD)	11.330612
Skewness	1.0011898
Sum	16299.338
Variance	358.5731
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
35	6	0.4%
22	6	0.4%
15.5	5	0.3%
37.5	5	0.3%
48	5	0.3%
16.99	4	0.3%
17.6	4	0.3%
23	4	0.3%
58	4	0.3%
18.8	4	0.3%
Other values (385)	516	32.9%
(Missing)	1007	64.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.2	1	0.1%
0.28	1	0.1%
0.3	1	0.1%
0.34	1	0.1%
0.37	1	0.1%
0.38	1	0.1%
0.39	1	0.1%
0.4	1	0.1%
0.414	1	0.1%
0.5	4	0.3%

Value	Count	Frequency (%)
90.5	1	0.1%
88.17	2	0.1%
87.42	2	0.1%
87.12	2	0.1%
86.8	2	0.1%
85.54022989	1	0.1%
83.93	3	0.2%
82.85	2	0.1%
82.72	3	0.2%
82	1	0.1%

NH3-N loss (%)
Real number (ℝ)

Distinct	687
Distinct (%)	82.1%
Missing	733
Missing (%)	46.7%
Infinite	0
Infinite (%)	0.0%
Mean	12.072503

Minimum	6.0941176 × 10^-6
Maximum	84.514977
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	12.4 KiB

Quantile statistics

Minimum	6.0941176 × 10^-6
5-th percentile	0.013294598
Q1	1.9344706
median	10.15
Q3	18.7
95-th percentile	32.4
Maximum	84.514977
Range	84.514971
Interquartile range (IQR)	16.765529

Descriptive statistics

Standard deviation	11.536968
Coefficient of variation (CV)	0.95564013
Kurtosis	4.5748549
Mean	12.072503
Median Absolute Deviation (MAD)	8.4520458
Skewness	1.5104163
Sum	10104.685
Variance	133.10163
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
22	8	0.5%
24.9	6	0.4%
12.7	6	0.4%
9.6	5	0.3%
13.3	5	0.3%
32.5	4	0.3%
9	4	0.3%
21.16	4	0.3%
18.7	4	0.3%
21.2	4	0.3%
Other values (677)	787	50.1%
(Missing)	733	46.7%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
6.094117647 × 10^-6	1	0.1%
8.53276788 × 10^-6	1	0.1%
2.890588235 × 10^-5	1	0.1%
5.312462729 × 10^-5	1	0.1%
6.207228026 × 10^-5	1	0.1%
9.369246562 × 10^-5	1	0.1%
0.0001839619463	1	0.1%
0.0002324113647	1	0.1%
0.0002882352941	1	0.1%
0.0003135858353	1	0.1%

Value	Count	Frequency (%)
84.51497682	1	0.1%
74.71149316	1	0.1%
74.5876815	1	0.1%
72.7944032	1	0.1%
65	1	0.1%
52.92898646	1	0.1%
50.9	2	0.1%
48.9	1	0.1%
47.9	1	0.1%
44.47	1	0.1%

N2O-N loss (%)
Real number (ℝ)

Distinct	414
Distinct (%)	72.5%
Missing	999
Missing (%)	63.6%
Infinite	0
Infinite (%)	0.0%
Mean	1.1660081

Minimum	-0.0031818182
Maximum	13.05
Zeros	0
Zeros (%)	0.0%
Negative	3
Negative (%)	0.2%
Memory size	12.4 KiB

Quantile statistics

Minimum	-0.0031818182
5-th percentile	0.00099272727
Q1	0.036272727
median	0.34
Q3	1.385
95-th percentile	5.46
Maximum	13.05
Range	13.053182
Interquartile range (IQR)	1.3487273

Descriptive statistics

Standard deviation	2.0478561
Coefficient of variation (CV)	1.7562965
Kurtosis	9.6611692
Mean	1.1660081
Median Absolute Deviation (MAD)	0.33669091
Skewness	2.9739283
Sum	665.79065
Variance	4.1937145
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.1	9	0.6%
1.4	9	0.6%
1	9	0.6%
1.5	9	0.6%
2	8	0.5%
1.2	7	0.4%
0.6	6	0.4%
0.09	4	0.3%
0.88	4	0.3%
0.2	4	0.3%
Other values (404)	502	32.0%
(Missing)	999	63.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
-0.003181818182	3	0.2%
0.0001718181818	1	0.1%
0.0002093636364	1	0.1%
0.0002208181818	1	0.1%
0.0002545454545	1	0.1%
0.0003181818182	1	0.1%
0.000329	1	0.1%
0.0003818181818	1	0.1%
0.0003964545455	1	0.1%
0.0003996363636	1	0.1%

Value	Count	Frequency (%)
13.05	1	0.1%
12.65063291	1	0.1%
11.22	1	0.1%
11.219	1	0.1%
10.1722	1	0.1%
9.9	1	0.1%
9.3	1	0.1%
9.27	1	0.1%
9.103448276	1	0.1%
8.92	1	0.1%

TC loss (%)
Real number (ℝ)

Distinct	306
Distinct (%)	69.9%
Missing	1132
Missing (%)	72.1%
Infinite	0
Infinite (%)	0.0%
Mean	42.426422

Minimum	5.1
Maximum	92.58
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	12.4 KiB

Quantile statistics

Minimum	5.1
5-th percentile	10.417
Q1	28.1
median	44.25
Q3	54
95-th percentile	72.79
Maximum	92.58
Range	87.48
Interquartile range (IQR)	25.9

Descriptive statistics

Standard deviation	18.655426
Coefficient of variation (CV)	0.43971244
Kurtosis	-0.39970277
Mean	42.426422
Median Absolute Deviation (MAD)	11.79
Skewness	0.03461062
Sum	18582.773
Variance	348.02491
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
50	8	0.5%
40	5	0.3%
44	5	0.3%
51	5	0.3%
53	4	0.3%
55	4	0.3%
43	4	0.3%
37.8	4	0.3%
59.23	4	0.3%
32	4	0.3%
Other values (296)	391	24.9%
(Missing)	1132	72.1%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
5.1	1	0.1%
5.54	1	0.1%
7	1	0.1%
7.04	1	0.1%
7.56	1	0.1%
7.81	1	0.1%
7.9	1	0.1%
8.1	1	0.1%
8.29	1	0.1%
8.3	1	0.1%

Value	Count	Frequency (%)
92.58	1	0.1%
90.5	1	0.1%
88.83	1	0.1%
88.75	1	0.1%
85.83	1	0.1%
83.52	2	0.1%
81.94	3	0.2%
80.91	2	0.1%
80.45	2	0.1%
80	1	0.1%

CH4-C loss (%)
Real number (ℝ)

Distinct	358
Distinct (%)	73.2%
Missing	1081
Missing (%)	68.9%
Infinite	0
Infinite (%)	0.0%
Mean	2.1898024

Minimum	0.000735
Maximum	59.34268
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	12.4 KiB

Quantile statistics

Minimum	0.000735
5-th percentile	0.0036615
Q1	0.062867625
median	0.32775
Q3	1.66
95-th percentile	7.6697974
Maximum	59.34268
Range	59.341945
Interquartile range (IQR)	1.5971324

Descriptive statistics

Standard deviation	6.1210631
Coefficient of variation (CV)	2.7952582
Kurtosis	41.130019
Mean	2.1898024
Median Absolute Deviation (MAD)	0.30906
Skewness	5.9267407
Sum	1070.8134
Variance	37.467414
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1.7	7	0.4%
0.05	7	0.4%
0.01	7	0.4%
0.4	6	0.4%
0.8	6	0.4%
0.34	6	0.4%
0.03	6	0.4%
0.6	5	0.3%
0.06	5	0.3%
0.09	4	0.3%
Other values (348)	430	27.4%
(Missing)	1081	68.9%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.000735	1	0.1%
0.00089616685	1	0.1%
0.0009	1	0.1%
0.0010125	1	0.1%
0.00105	1	0.1%
0.001132061802	2	0.1%
0.001166	1	0.1%
0.0012	1	0.1%
0.00124185	1	0.1%
0.0012666	1	0.1%

Value	Count	Frequency (%)
59.34267964	1	0.1%
55.12008912	1	0.1%
44.54663189	1	0.1%
40.60705682	1	0.1%
38.70519299	1	0.1%
35.59202304	1	0.1%
35.15051894	1	0.1%
32.87507472	1	0.1%
27.21476571	1	0.1%
25.2	1	0.1%

CO2-C loss (%)
Real number (ℝ)

Distinct	191
Distinct (%)	93.6%
Missing	1366
Missing (%)	87.0%
Infinite	0
Infinite (%)	0.0%
Mean	24.952775

Minimum	-0.065865414
Maximum	234.43559
Zeros	0
Zeros (%)	0.0%
Negative	3
Negative (%)	0.2%
Memory size	12.4 KiB

Quantile statistics

Minimum	-0.065865414
5-th percentile	0.54272727
Q1	5.2873818
median	17.290363
Q3	36.1
95-th percentile	66.594462
Maximum	234.43559
Range	234.50146
Interquartile range (IQR)	30.812618

Descriptive statistics

Standard deviation	28.188795
Coefficient of variation (CV)	1.1296858
Kurtosis	17.171108
Mean	24.952775
Median Absolute Deviation (MAD)	14.181272
Skewness	3.1817408
Sum	5090.366
Variance	794.60816
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
25	2	0.1%
31.4	2	0.1%
13.9	2	0.1%
23.9	2	0.1%
0.0004116588369	2	0.1%
-0.06586541391	2	0.1%
33.3	2	0.1%
42.4	2	0.1%
45.6	2	0.1%
32.1	2	0.1%
Other values (181)	184	11.7%
(Missing)	1366	87.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
-0.06586541391	2	0.1%
-0.03293270695	1	0.1%
0.0004116588369	2	0.1%
0.1237580455	1	0.1%
0.1868503909	1	0.1%
0.1934796534	1	0.1%
0.2727272727	1	0.1%
0.3	1	0.1%
0.5181818182	1	0.1%
0.6818181818	1	0.1%

Value	Count	Frequency (%)
234.435591	1	0.1%
154.6684582	1	0.1%
130.9322097	1	0.1%
111.3495988	1	0.1%
109.2624885	1	0.1%
85.08164841	1	0.1%
82.96572199	1	0.1%
74.18915559	1	0.1%
73.43993651	1	0.1%
67.92370809	1	0.1%

Methods
Categorical

Distinct	4
Distinct (%)	0.5%
Missing	711
Missing (%)	45.3%
Memory size	12.4 KiB

Reactor	576
Static	227
Windrow	32
Turning	24

Length

Max length	7
Median length	7
Mean length	6.7357392
Min length	6

Characters and Unicode

Total characters	5786
Distinct characters	16
Distinct categories	2 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Reactor
2nd row	Reactor
3rd row	Reactor
4th row	Reactor
5th row	Reactor

Common Values

Value	Count	Frequency (%)
Reactor	576	36.7%
Static	227	14.5%
Windrow	32	2.0%
Turning	24	1.5%
(Missing)	711	45.3%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
reactor	576	67.1%
static	227	26.4%
windrow	32	3.7%
turning	24	2.8%

Most occurring characters

Value	Count	Frequency (%)
t	1030	17.8%
a	803	13.9%
c	803	13.9%
r	632	10.9%
o	608	10.5%
R	576	10.0%
e	576	10.0%
i	283	4.9%
S	227	3.9%
n	80	1.4%
Other values (6)	168	2.9%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	4927	85.2%
Uppercase Letter	859	14.8%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
t	1030	20.9%
a	803	16.3%
c	803	16.3%
r	632	12.8%
o	608	12.3%
e	576	11.7%
i	283	5.7%
n	80	1.6%
d	32	0.6%
w	32	0.6%
Other values (2)	48	1.0%

Uppercase Letter

Value	Count	Frequency (%)
R	576	67.1%
S	227	26.4%
W	32	3.7%
T	24	2.8%

Most occurring scripts

Value	Count	Frequency (%)
Latin	5786	100.0%

Most frequent character per script

Latin

Value	Count	Frequency (%)
t	1030	17.8%
a	803	13.9%
c	803	13.9%
r	632	10.9%
o	608	10.5%
R	576	10.0%
e	576	10.0%
i	283	4.9%
S	227	3.9%
n	80	1.4%
Other values (6)	168	2.9%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	5786	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
t	1030	17.8%
a	803	13.9%
c	803	13.9%
r	632	10.9%
o	608	10.5%
R	576	10.0%
e	576	10.0%
i	283	4.9%
S	227	3.9%
n	80	1.4%
Other values (6)	168	2.9%

Time Period
Unsupported

MISSING REJECTED UNSUPPORTED

Missing	905
Missing (%)	57.6%
Memory size	12.4 KiB

堆体大小（m3)
Real number (ℝ)

Distinct	50
Distinct (%)	33.8%
Missing	1422
Missing (%)	90.6%
Infinite	0
Infinite (%)	0.0%
Mean	4.3778926

Minimum	0.0035
Maximum	202.5
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	12.4 KiB

Quantile statistics

Minimum	0.0035
5-th percentile	0.01
Q1	0.06
median	0.3235
Q3	1.252
95-th percentile	10
Maximum	202.5
Range	202.4965
Interquartile range (IQR)	1.192

Descriptive statistics

Standard deviation	21.089674
Coefficient of variation (CV)	4.817312
Kurtosis	64.742818
Mean	4.3778926
Median Absolute Deviation (MAD)	0.3135
Skewness	7.7411719
Sum	647.9281
Variance	444.77436
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.06	24	1.5%
0.03	10	0.6%
1.37	10	0.6%
0.01	9	0.6%
1.2	8	0.5%
0.1	7	0.4%
1	6	0.4%
1.12	6	0.4%
10	5	0.3%
0.2	4	0.3%
Other values (40)	59	3.8%
(Missing)	1422	90.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.0035	1	0.1%
0.01	9	0.6%
0.026	1	0.1%
0.03	10	0.6%
0.0318	1	0.1%
0.032	1	0.1%
0.0488	1	0.1%
0.049	1	0.1%
0.06	24	1.5%
0.08	1	0.1%

Value	Count	Frequency (%)
202.5	1	0.1%
140	1	0.1%
63	1	0.1%
36	2	0.1%
11.25	2	0.1%
10	5	0.3%
9.75	2	0.1%
4.5	1	0.1%
2	1	0.1%
1.9	3	0.2%

初始容重（kgL）
Real number (ℝ)

Distinct	74
Distinct (%)	54.0%
Missing	1433
Missing (%)	91.3%
Infinite	0
Infinite (%)	0.0%
Mean	0.4659708

Minimum	0.05
Maximum	1.4285
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	12.4 KiB

Quantile statistics

Minimum	0.05
5-th percentile	0.1
Q1	0.3
median	0.444
Q3	0.616
95-th percentile	0.926
Maximum	1.4285
Range	1.3785
Interquartile range (IQR)	0.316

Descriptive statistics

Standard deviation	0.27278441
Coefficient of variation (CV)	0.58541095
Kurtosis	0.63033
Mean	0.4659708
Median Absolute Deviation (MAD)	0.1565
Skewness	0.80200289
Sum	63.838
Variance	0.074411334
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.5	12	0.8%
0.305	8	0.5%
0.4	6	0.4%
0.123	6	0.4%
0.3	6	0.4%
0.1	5	0.3%
0.492	4	0.3%
0.667	4	0.3%
0.1715	4	0.3%
0.616	3	0.2%
Other values (64)	79	5.0%
(Missing)	1433	91.3%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.05	2	0.1%
0.073	2	0.1%
0.099	2	0.1%
0.1	5	0.3%
0.11	1	0.1%
0.123	6	0.4%
0.14	2	0.1%
0.1715	4	0.3%
0.21	1	0.1%
0.229	1	0.1%

Value	Count	Frequency (%)
1.4285	1	0.1%
1.274	1	0.1%
1.105	1	0.1%
1.061	2	0.1%
1.033	1	0.1%
0.95	1	0.1%
0.92	1	0.1%
0.891	1	0.1%
0.89	1	0.1%
0.886	1	0.1%

Ventilation
Categorical

Distinct	3
Distinct (%)	0.7%
Missing	1156
Missing (%)	73.6%
Memory size	12.4 KiB

force aeration+turning	263
turning	94
force aeration	57

Length

Max length	22
Median length	22
Mean length	17.492754
Min length	7

Characters and Unicode

Total characters	7242
Distinct characters	13
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	force aeration+turning
2nd row	force aeration+turning
3rd row	force aeration+turning
4th row	force aeration+turning
5th row	force aeration+turning

Common Values

Value	Count	Frequency (%)
force aeration+turning	263	16.8%
turning	94	6.0%
force aeration	57	3.6%
(Missing)	1156	73.6%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
force	320	43.6%
aeration+turning	263	35.8%
turning	94	12.8%
aeration	57	7.8%

Most occurring characters

Value	Count	Frequency (%)
n	1034	14.3%
r	997	13.8%
t	677	9.3%
i	677	9.3%
o	640	8.8%
e	640	8.8%
a	640	8.8%
u	357	4.9%
g	357	4.9%
f	320	4.4%
Other values (3)	903	12.5%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	6659	91.9%
Space Separator	320	4.4%
Math Symbol	263	3.6%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
n	1034	15.5%
r	997	15.0%
t	677	10.2%
i	677	10.2%
o	640	9.6%
e	640	9.6%
a	640	9.6%
u	357	5.4%
g	357	5.4%
f	320	4.8%

Space Separator

Value	Count	Frequency (%)
	320	100.0%

Math Symbol

Value	Count	Frequency (%)
+	263	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	6659	91.9%
Common	583	8.1%

Most frequent character per script

Latin

Value	Count	Frequency (%)
n	1034	15.5%
r	997	15.0%
t	677	10.2%
i	677	10.2%
o	640	9.6%
e	640	9.6%
a	640	9.6%
u	357	5.4%
g	357	5.4%
f	320	4.8%

Common

Value	Count	Frequency (%)
	320	54.9%
+	263	45.1%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	7242	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
n	1034	14.3%
r	997	13.8%
t	677	9.3%
i	677	9.3%
o	640	8.8%
e	640	8.8%
a	640	8.8%
u	357	4.9%
g	357	4.9%
f	320	4.4%
Other values (3)	903	12.5%

通风速率（L min-1 kg DW）
Unsupported

MISSING REJECTED UNSUPPORTED

Missing	1287
Missing (%)	82.0%
Memory size	12.4 KiB

Peak Temperature (℃）
Real number (ℝ)

Distinct	95
Distinct (%)	76.0%
Missing	1445
Missing (%)	92.0%
Infinite	0
Infinite (%)	0.0%
Mean	57.37624

Minimum	29.55
Maximum	79
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	12.4 KiB

Quantile statistics

Minimum	29.55
5-th percentile	37.64
Q1	51.6
median	57.9
Q3	65.5
95-th percentile	71.86
Maximum	79
Range	49.45
Interquartile range (IQR)	13.9

Descriptive statistics

Standard deviation	10.498781
Coefficient of variation (CV)	0.18298133
Kurtosis	-0.23279112
Mean	57.37624
Median Absolute Deviation (MAD)	7.1
Skewness	-0.54517236
Sum	7172.03
Variance	110.22439
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
53	4	0.3%
54	4	0.3%
51	3	0.2%
56	3	0.2%
64.4	3	0.2%
56.5	3	0.2%
50	3	0.2%
53.5	3	0.2%
68	2	0.1%
35	2	0.1%
Other values (85)	95	6.1%
(Missing)	1445	92.0%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
29.55	1	0.1%
33	1	0.1%
33.4	1	0.1%
35	2	0.1%
37.2	1	0.1%
37.6	1	0.1%
37.8	1	0.1%
38.1	1	0.1%
39	1	0.1%
39.1	1	0.1%

Value	Count	Frequency (%)
79	1	0.1%
75	1	0.1%
74	1	0.1%
73	1	0.1%
72.7	1	0.1%
72.2	1	0.1%
72	1	0.1%
71.3	1	0.1%
71	1	0.1%
70.77	1	0.1%

Average Temperature (℃）
Real number (ℝ)

Distinct	59
Distinct (%)	80.8%
Missing	1497
Missing (%)	95.4%
Infinite	0
Infinite (%)	0.0%
Mean	38.027397

Minimum	-13.23
Maximum	65
Zeros	0
Zeros (%)	0.0%
Negative	1
Negative (%)	0.1%
Memory size	12.4 KiB

Quantile statistics

Minimum	-13.23
5-th percentile	13.93
Q1	24.4
median	37.74
Q3	59.39
95-th percentile	65
Maximum	65
Range	78.23
Interquartile range (IQR)	34.99

Descriptive statistics

Standard deviation	18.382047
Coefficient of variation (CV)	0.48338958
Kurtosis	-0.63151884
Mean	38.027397
Median Absolute Deviation (MAD)	14.32
Skewness	-0.073591761
Sum	2776
Variance	337.89967
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
65	9	0.6%
32	4	0.3%
41.12	2	0.1%
60	2	0.1%
60.08	2	0.1%
38.98	1	0.1%
35.76	1	0.1%
40.83	1	0.1%
14.83	1	0.1%
40.72	1	0.1%
Other values (49)	49	3.1%
(Missing)	1497	95.4%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
-13.23	1	0.1%
5	1	0.1%
11	1	0.1%
12.58	1	0.1%
14.83	1	0.1%
15	1	0.1%
15.08	1	0.1%
16.01	1	0.1%
16.22	1	0.1%
17.1	1	0.1%

Value	Count	Frequency (%)
65	9	0.6%
62.42	1	0.1%
61	1	0.1%
60.4	1	0.1%
60.19	1	0.1%
60.08	2	0.1%
60.04	1	0.1%
60	2	0.1%
59.39	1	0.1%
55	1	0.1%

the ratio of treatment to control-TN
Real number (ℝ)

Distinct	188
Distinct (%)	95.4%
Missing	1373
Missing (%)	87.5%
Infinite	0
Infinite (%)	0.0%
Mean	0.6483094

Minimum	0.017094017
Maximum	3.2338308
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	12.4 KiB

Quantile statistics

Minimum	0.017094017
5-th percentile	0.14155844
Q1	0.40464345
median	0.66666667
Q3	0.8277512
95-th percentile	1.0313626
Maximum	3.2338308
Range	3.2167368
Interquartile range (IQR)	0.42310775

Descriptive statistics

Standard deviation	0.36662799
Coefficient of variation (CV)	0.56551392
Kurtosis	14.604485
Mean	0.6483094
Median Absolute Deviation (MAD)	0.19733333
Skewness	2.4893328
Sum	127.71695
Variance	0.13441608
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.68173258	2	0.1%
0.8757062147	2	0.1%
1	2	0.1%
0.2781	2	0.1%
0.87	2	0.1%
0.1347	2	0.1%
0.3594	2	0.1%
0.7380952381	2	0.1%
0.5013333333	2	0.1%
0.4	1	0.1%
Other values (178)	178	11.3%
(Missing)	1373	87.5%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.01709401709	1	0.1%
0.01769230769	1	0.1%
0.0235042735	1	0.1%
0.02857142857	1	0.1%
0.03846153846	1	0.1%
0.0438	1	0.1%
0.1108	1	0.1%
0.1347	2	0.1%
0.1363636364	1	0.1%
0.1428571429	1	0.1%

Value	Count	Frequency (%)
3.233830846	1	0.1%
2.304250049	1	0.1%
2.154228856	1	0.1%
1.555070423	1	0.1%
1.365853659	1	0.1%
1.170731707	1	0.1%
1.153609831	1	0.1%
1.088801331	1	0.1%
1.067588326	1	0.1%
1.039987504	1	0.1%

the ratio of treatment to control-NH3
Real number (ℝ)

Distinct	194
Distinct (%)	96.5%
Missing	1369
Missing (%)	87.2%
Infinite	0
Infinite (%)	0.0%
Mean	0.73089207

Minimum	0.017857143
Maximum	6.1666667
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	12.4 KiB

Quantile statistics

Minimum	0.017857143
5-th percentile	0.14285714
Q1	0.4137931
median	0.63793236
Q3	0.79548989
95-th percentile	1.3040528
Maximum	6.1666667
Range	6.1488095
Interquartile range (IQR)	0.38169679

Descriptive statistics

Standard deviation	0.75477181
Coefficient of variation (CV)	1.032672
Kurtosis	31.529311
Mean	0.73089207
Median Absolute Deviation (MAD)	0.18869541
Skewness	5.1865537
Sum	146.90931
Variance	0.56968048
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.4107142857	2	0.1%
1.078947368	2	0.1%
0.7	2	0.1%
0.4461538462	2	0.1%
0.7777777778	2	0.1%
0.74	2	0.1%
0.1078431373	2	0.1%
0.623	1	0.1%
0.347826087	1	0.1%
0.8975903614	1	0.1%
Other values (184)	184	11.7%
(Missing)	1369	87.2%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.01785714286	1	0.1%
0.01960784314	1	0.1%
0.03921568627	1	0.1%
0.05882352941	1	0.1%
0.0625	1	0.1%
0.09523809524	1	0.1%
0.1	1	0.1%
0.1078431373	2	0.1%
0.12	1	0.1%
0.1428571429	1	0.1%

Value	Count	Frequency (%)
6.166666667	1	0.1%
5.633333333	1	0.1%
5.483333333	1	0.1%
4.5	1	0.1%
2.398311049	1	0.1%
1.758506616	1	0.1%
1.686206897	1	0.1%
1.585635359	1	0.1%
1.547169811	1	0.1%
1.533333333	1	0.1%

the ratio of treatment to control-N2O
Real number (ℝ)

Distinct	91
Distinct (%)	91.9%
Missing	1471
Missing (%)	93.7%
Infinite	0
Infinite (%)	0.0%
Mean	0.84587617

Minimum	0.008
Maximum	5.96
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	12.4 KiB

Quantile statistics

Minimum	0.008
5-th percentile	0.027588556
Q1	0.36683488
median	0.79489796
Q3	1.0512957
95-th percentile	1.7686862
Maximum	5.96
Range	5.952
Interquartile range (IQR)	0.68446085

Descriptive statistics

Standard deviation	0.72974898
Coefficient of variation (CV)	0.86271372
Kurtosis	24.040143
Mean	0.84587617
Median Absolute Deviation (MAD)	0.3227491
Skewness	3.7433216
Sum	83.741741
Variance	0.53253357
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.9333333333	4	0.3%
0.8	4	0.3%
0.76	2	0.1%
0.9	2	0.1%
1.382352941	1	0.1%
0.534	1	0.1%
0.02452316076	1	0.1%
0.9804878049	1	0.1%
0.7196041763	1	0.1%
0.164	1	0.1%
Other values (81)	81	5.2%
(Missing)	1471	93.7%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.008	1	0.1%
0.01219346049	1	0.1%
0.02	1	0.1%
0.02077656676	1	0.1%
0.02452316076	1	0.1%
0.02792915531	1	0.1%
0.036	1	0.1%
0.05704099822	1	0.1%
0.147	1	0.1%
0.1474	1	0.1%

Value	Count	Frequency (%)
5.96	1	0.1%
2.566334992	1	0.1%
2.345771144	1	0.1%
1.98630137	1	0.1%
1.782752902	1	0.1%
1.767123288	1	0.1%
1.727197347	1	0.1%
1.667	1	0.1%
1.583333333	1	0.1%
1.501	1	0.1%

the ratio of treatment to control-CH4
Real number (ℝ)

Distinct	65
Distinct (%)	94.2%
Missing	1501
Missing (%)	95.6%
Infinite	0
Infinite (%)	0.0%
Mean	0.55437993

Minimum	0.0073751257
Maximum	2.6976744
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	12.4 KiB

Quantile statistics

Minimum	0.0073751257
5-th percentile	0.018095946
Q1	0.18
median	0.5277
Q3	0.78145606
95-th percentile	1.1092437
Maximum	2.6976744
Range	2.6902993
Interquartile range (IQR)	0.60145606

Descriptive statistics

Standard deviation	0.49014141
Coefficient of variation (CV)	0.88412546
Kurtosis	6.4941137
Mean	0.55437993
Median Absolute Deviation (MAD)	0.33688333
Skewness	1.9610525
Sum	38.252215
Variance	0.2402386
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0.2727272727	2	0.1%
1.058823529	2	0.1%
0.12	2	0.1%
0.7814560596	2	0.1%
0.6767676768	1	0.1%
1.047619048	1	0.1%
1.153846154	1	0.1%
0.225	1	0.1%
0.5588235294	1	0.1%
0.1473438409	1	0.1%
Other values (55)	55	3.5%
(Missing)	1501	95.6%

Minimum 10 values
Maximum 10 values

Value	Count	Frequency (%)
0.007375125712	1	0.1%
0.008380824673	1	0.1%
0.01005698961	1	0.1%
0.01106268857	1	0.1%
0.02864583333	1	0.1%
0.03	1	0.1%
0.033203125	1	0.1%
0.047	1	0.1%
0.05	1	0.1%
0.1155	1	0.1%

Value	Count	Frequency (%)
2.697674419	1	0.1%
2.406417112	1	0.1%
1.153846154	1	0.1%
1.142857143	1	0.1%
1.058823529	2	0.1%
1.047619048	1	0.1%
1.045859305	1	0.1%
1	1	0.1%
0.9433333333	1	0.1%
0.9117647059	1	0.1%

Scale
Categorical

Distinct	6
Distinct (%)	0.6%
Missing	581
Missing (%)	37.0%
Memory size	12.4 KiB

lab	526
pilot	169
lab	154
Lab	79
Field	58

Length

Max length	11
Median length	3
Mean length	3.6390293
Min length	3

Characters and Unicode

Total characters	3599
Distinct characters	16
Distinct categories	3 ?
Distinct scripts	2 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	lab
2nd row	lab
3rd row	lab
4th row	lab
5th row	lab

Common Values

Value	Count	Frequency (%)
lab	526	33.5%
pilot	169	10.8%
lab	154	9.8%
Lab	79	5.0%
Field	58	3.7%
Large scale	3	0.2%
(Missing)	581	37.0%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
lab	759	76.5%
pilot	169	17.0%
field	58	5.8%
large	3	0.3%
scale	3	0.3%

Most occurring characters

Value	Count	Frequency (%)
l	910	25.3%
a	765	21.3%
b	759	21.1%
i	227	6.3%
p	169	4.7%
o	169	4.7%
t	169	4.7%
	157	4.4%
L	82	2.3%
e	64	1.8%
Other values (6)	128	3.6%

Most occurring categories

Value	Count	Frequency (%)
Lowercase Letter	3302	91.7%
Space Separator	157	4.4%
Uppercase Letter	140	3.9%

Most frequent character per category

Lowercase Letter

Value	Count	Frequency (%)
l	910	27.6%
a	765	23.2%
b	759	23.0%
i	227	6.9%
p	169	5.1%
o	169	5.1%
t	169	5.1%
e	64	1.9%
d	58	1.8%
r	3	0.1%
Other values (3)	9	0.3%

Uppercase Letter

Value	Count	Frequency (%)
L	82	58.6%
F	58	41.4%

Space Separator

Value	Count	Frequency (%)
	157	100.0%

Most occurring scripts

Value	Count	Frequency (%)
Latin	3442	95.6%
Common	157	4.4%

Most frequent character per script

Latin

Value	Count	Frequency (%)
l	910	26.4%
a	765	22.2%
b	759	22.1%
i	227	6.6%
p	169	4.9%
o	169	4.9%
t	169	4.9%
L	82	2.4%
e	64	1.9%
F	58	1.7%
Other values (5)	70	2.0%

Common

Value	Count	Frequency (%)
	157	100.0%

Most occurring blocks

Value	Count	Frequency (%)
ASCII	3599	100.0%

Most frequent character per block

ASCII

Value	Count	Frequency (%)
l	910	25.3%
a	765	21.3%
b	759	21.1%
i	227	6.3%
p	169	4.7%
o	169	4.7%
t	169	4.7%
	157	4.4%
L	82	2.3%
e	64	1.8%
Other values (6)	128	3.6%

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

First rows
Last rows

	id	title	author	location	Journal	material_0	material_1	Excipients	Additive Species	Additive_1	Additive_2	Application Rate (%)	initial moisture content(%)	initial pH	initial TN(%)	initial TC(%)	initial CN(%)	TN loss (%)	NH3-N loss (%)	N2O-N loss (%)	TC loss (%)	CH4-C loss (%)	CO2-C loss (%)	Methods	Time Period	堆体大小（m3)	初始容重（kgL）	Ventilation	通风速率（L min-1 kg DW）	Peak Temperature (℃）	Average Temperature (℃）	the ratio of treatment to control-TN	the ratio of treatment to control-NH3	the ratio of treatment to control-N2O	the ratio of treatment to control-CH4	Scale
0	1	NaN	Limei Ren et al.,2010	China	waste management	Manure	Swine manure	NaN	NaN	NaN	NaN	NaN	65.0	7.60664	2.66	39.90	15.000000	35.0	28.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	force aeration+turning	NaN	NaN	NaN	NaN	NaN	NaN	NaN	lab
1	1	NaN	Limei Ren et al.,2010	China	waste management	Manure	Swine manure	NaN	Chemical	PO43- and Mg2+ salts	NaN	15.4	NaN	7.41084	NaN	NaN	NaN	12.0	9.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	force aeration+turning	NaN	NaN	NaN	0.342857	0.321429	NaN	NaN	lab
2	1	NaN	Limei Ren et al.,2010	China	waste management	Manure	Swine manure	NaN	Chemical	PO43- and Mg2+ salts	NaN	18.7	NaN	6.61538	NaN	NaN	NaN	5.0	4.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	force aeration+turning	NaN	NaN	NaN	0.142857	0.142857	NaN	NaN	lab
3	1	NaN	Limei Ren et al.,2010	China	waste management	Manure	Swine manure	NaN	Chemical	PO43- and Mg2+ salts	NaN	17.1	NaN	6.40734	NaN	NaN	NaN	1.0	0.5	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	force aeration+turning	NaN	NaN	NaN	0.028571	0.017857	NaN	NaN	lab
4	2	NaN	Khalil Tubail et al.,2008	US	compost science & utilization	Manure	Cow manure	NaN	NaN	NaN	NaN	NaN	NaN	7.52000	1.31	47.16	36.000000	16.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	force aeration+turning	NaN	NaN	NaN	NaN	NaN	NaN	NaN	lab
5	2	NaN	Khalil Tubail et al.,2008	US	compost science & utilization	Manure	Cow manure	NaN	Physical	gypsum	NaN	NaN	NaN	7.58000	NaN	NaN	NaN	6.1	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	force aeration+turning	NaN	NaN	NaN	0.381250	NaN	NaN	NaN	lab
6	2	NaN	Khalil Tubail et al.,2008	US	compost science & utilization	Sewage sludge	NaN	NaN	NaN	NaN	NaN	NaN	NaN	7.70000	2.85	54.15	19.000000	25.1	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	force aeration+turning	NaN	NaN	NaN	NaN	NaN	NaN	NaN	lab
7	2	NaN	Khalil Tubail et al.,2008	US	compost science & utilization	Sewage sludge	NaN	NaN	Physical	gypsum	NaN	NaN	NaN	7.40000	NaN	NaN	NaN	11.4	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	force aeration+turning	NaN	NaN	NaN	0.454183	NaN	NaN	NaN	lab
8	3	NaN	Jishao Jiang et al.,2014	China	waste management	Manure	Swine manure	NaN	NaN	NaN	NaN	NaN	65.0	6.49842	2.46	32.50	13.211382	58.0	3.0	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	force aeration+turning	NaN	NaN	NaN	NaN	NaN	NaN	NaN	lab
9	3	NaN	Jishao Jiang et al.,2014	China	waste management	Manure	Swine manure	NaN	Physical	bentonite	NaN	NaN	NaN	7.20000	2.75	30.13	10.956364	50.3	4.6	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	force aeration+turning	NaN	NaN	NaN	0.867241	1.533333	NaN	NaN	lab

	id	title	author	location	Journal	material_0	material_1	Excipients	Additive Species	Additive_1	Additive_2	Application Rate (%)	initial moisture content(%)	initial pH	initial TN(%)	initial TC(%)	initial CN(%)	TN loss (%)	NH3-N loss (%)	N2O-N loss (%)	TC loss (%)	CH4-C loss (%)	CO2-C loss (%)	Methods	Time Period	堆体大小（m3)	初始容重（kgL）	Ventilation	通风速率（L min-1 kg DW）	Peak Temperature (℃）	Average Temperature (℃）	the ratio of treatment to control-TN	the ratio of treatment to control-NH3	the ratio of treatment to control-N2O	the ratio of treatment to control-CH4	Scale
1560	435	碳源调控对污泥堆肥过程氮素损失的影响及其作用机制	NaN	中国/黑龙江/哈尔滨	NaN	Sewage sludge	NaN	蔗糖	NaN	NaN	NaN	NaN	63.13	7.07	NaN	NaN	NaN	NaN	29.842400	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	0.2	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1561	435	碳源调控对污泥堆肥过程氮素损失的影响及其作用机制	NaN	中国/黑龙江/哈尔滨	NaN	Sewage sludge	NaN	蔗糖+秸秆	NaN	NaN	NaN	NaN	57.52	6.55	NaN	NaN	NaN	NaN	9.144800	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	0.2	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1562	435	碳源调控对污泥堆肥过程氮素损失的影响及其作用机制	NaN	中国/黑龙江/哈尔滨	NaN	Sewage sludge	NaN	蔗糖+秸秆	NaN	NaN	NaN	NaN	61.07	7.29	NaN	NaN	NaN	NaN	7.915800	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	0.2	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1563	435	碳源调控对污泥堆肥过程氮素损失的影响及其作用机制	NaN	中国/黑龙江/哈尔滨	NaN	Sewage sludge	NaN	蔗糖+秸秆	NaN	NaN	NaN	NaN	60.61	7.39	NaN	NaN	NaN	NaN	5.054400	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	0.2	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1564	435	碳源调控对污泥堆肥过程氮素损失的影响及其作用机制	NaN	中国/黑龙江/哈尔滨	NaN	Sewage sludge	NaN	蔗糖+秸秆	NaN	NaN	NaN	NaN	59.85	7.29	NaN	NaN	NaN	NaN	14.817600	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	0.2	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1565	435	碳源调控对污泥堆肥过程氮素损失的影响及其作用机制	NaN	中国/黑龙江/哈尔滨	NaN	Sewage sludge	NaN	蔗糖+秸秆	NaN	NaN	NaN	NaN	60.99	7.30	NaN	NaN	NaN	NaN	23.287500	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	0.2	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1566	436	原位固氮剂在污泥堆肥过程中保氮机制	NaN	中国/河南/新乡	NaN	Sewage sludge	NaN	木屑	NaN	NaN	NaN	NaN	NaN	7.44	NaN	NaN	NaN	NaN	2.691121	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	80mL/min	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1567	436	原位固氮剂在污泥堆肥过程中保氮机制	NaN	中国/河南/新乡	NaN	Sewage sludge	NaN	木屑+MgSO4	NaN	NaN	NaN	NaN	NaN	7.20	NaN	NaN	NaN	NaN	1.593054	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	80mL/min	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1568	436	原位固氮剂在污泥堆肥过程中保氮机制	NaN	中国/河南/新乡	NaN	Sewage sludge	NaN	木屑+KPM	NaN	NaN	NaN	NaN	NaN	7.09	NaN	NaN	NaN	NaN	1.869247	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	80mL/min	NaN	NaN	NaN	NaN	NaN	NaN	NaN
1569	436	原位固氮剂在污泥堆肥过程中保氮机制	NaN	中国/河南/新乡	NaN	Sewage sludge	NaN	木屑+KP	NaN	NaN	NaN	NaN	NaN	7.44	NaN	NaN	NaN	NaN	3.858471	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	80mL/min	NaN	NaN	NaN	NaN	NaN	NaN	NaN

Most frequently occurring

	id	title	author	location	Journal	material_0	material_1	Excipients	Additive Species	Additive_1	Additive_2	Application Rate (%)	initial moisture content(%)	initial pH	initial TN(%)	initial TC(%)	initial CN(%)	TN loss (%)	NH3-N loss (%)	N2O-N loss (%)	TC loss (%)	CH4-C loss (%)	CO2-C loss (%)	Methods	堆体大小（m3)	初始容重（kgL）	Ventilation	Peak Temperature (℃）	Average Temperature (℃）	the ratio of treatment to control-TN	the ratio of treatment to control-NH3	the ratio of treatment to control-N2O	the ratio of treatment to control-CH4	Scale	# duplicates
37	173	Nitrogen loss in chicken litter compost as affected by carbon to nitrogen ratio and turning frequency	Ogunwande et al., 2008	NaN	Bioresource Technology	Manure	Poultry manure	Sawdust	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	20.0	82.72	NaN	NaN	72.20	NaN	NaN	Static	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	pilot	3
40	173	Nitrogen loss in chicken litter compost as affected by carbon to nitrogen ratio and turning frequency	Ogunwande et al., 2008	NaN	Bioresource Technology	Manure	Poultry manure	Sawdust	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	25.0	70.73	NaN	NaN	72.40	NaN	NaN	Static	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	pilot	3
44	173	Nitrogen loss in chicken litter compost as affected by carbon to nitrogen ratio and turning frequency	Ogunwande et al., 2008	NaN	Bioresource Technology	Manure	Poultry manure	Sawdust	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	30.0	83.93	NaN	NaN	81.94	NaN	NaN	Static	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	pilot	3
0	28	NaN	Leimei Ren et al.,2009	China	Journal of Agro-Environment Science (in Chinese)	Manure	Poultry manure	NaN	Chemical	PO43- and Mg2+ salts	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	turning	NaN	NaN	0.1347	NaN	NaN	NaN	lab	2
1	28	NaN	Leimei Ren et al.,2009	China	Journal of Agro-Environment Science (in Chinese)	Manure	Poultry manure	NaN	Chemical	PO43- and Mg2+ salts	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	turning	NaN	NaN	0.2781	NaN	NaN	NaN	lab	2
2	28	NaN	Leimei Ren et al.,2009	China	Journal of Agro-Environment Science (in Chinese)	Manure	Poultry manure	NaN	Chemical	PO43- and Mg2+ salts	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	turning	NaN	NaN	0.3594	NaN	NaN	NaN	lab	2
3	119	Biochar combined with gypsum reduces both nitrogen and carbon losses during agricultural waste composting and enhances overall compost quality by regulating microbial activities and functions	Qu et al., 2020	NaN	Bioresource Technology	Manure	Poultry manure	Plant straw	Physical	Biochar	NaN	5.0	60.0	7.48	1.63	48.9	30.0	16.99	NaN	NaN	40.50	NaN	NaN	Reactor	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	lab	2
4	119	Biochar combined with gypsum reduces both nitrogen and carbon losses during agricultural waste composting and enhances overall compost quality by regulating microbial activities and functions	Qu et al., 2020	NaN	Bioresource Technology	Manure	Poultry manure	Plant straw	Physical	Biochar	NaN	5.0	60.0	7.69	1.78	44.5	25.0	18.35	NaN	NaN	30.60	NaN	NaN	Reactor	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	lab	2
5	119	Biochar combined with gypsum reduces both nitrogen and carbon losses during agricultural waste composting and enhances overall compost quality by regulating microbial activities and functions	Qu et al., 2020	NaN	Bioresource Technology	Manure	Poultry manure	Plant straw	Physical	Biochar	NaN	5.0	60.0	7.90	2.02	40.4	20.0	28.54	NaN	NaN	37.80	NaN	NaN	Reactor	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	lab	2
6	119	Biochar combined with gypsum reduces both nitrogen and carbon losses during agricultural waste composting and enhances overall compost quality by regulating microbial activities and functions	Qu et al., 2020	NaN	Bioresource Technology	Manure	Poultry manure	Plant straw	Physical	Gypsum	NaN	5.0	60.0	7.13	1.70	51.0	30.0	8.15	NaN	NaN	37.80	NaN	NaN	Reactor	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	NaN	lab	2

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Other Letter

Lowercase Letter

Uppercase Letter

Decimal Number

Other Punctuation

Dash Punctuation

Other Number

Space Separator

Close Punctuation

Open Punctuation

Initial Punctuation

Final Punctuation

Most occurring scripts

Most frequent character per script

Han

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

CJK

None

Punctuation

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Decimal Number

Other Punctuation

Space Separator

Dash Punctuation

Most occurring scripts

Most frequent character per script

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

None

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Other Letter

Lowercase Letter

Uppercase Letter

Other Punctuation

Space Separator

Most occurring scripts

Most frequent character per script

Han

Latin

Common

Most occurring blocks

Most frequent character per block

ASCII

CJK

None

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Lowercase Letter

Uppercase Letter

Other Punctuation

Decimal Number

Space Separator

Close Punctuation